Abstract: 【Objective】With respect to the change detection on wetlands, very high spatial resolution images of drained managed wetland ponds were used, which could provide more information for further management. 【Method】 The proposed method is based on pixel-oriented difference image and object-based post-classification(OB-M). Multivariate alteration detection (MAD) transformation was used to get the extended difference image, and object-based decision tree classification was applied on MAD components to detect the true change information of difference image, which had a very significant shape feature.【Result】 The proposed OB-MAD can successfully detect the false change information, such as the inevitable mis-registration, shadow and vegetation phenology differences. Compared with the traditional MAD method with thresholds (Threshold-MAD) and the traditional object-based post-classification method (OB-T), the proposed OB-M method produced the highest accuracy, which took advantage of both pixel- and object-based technology.【Conclusion】Results indicated that the object-based post-classification on MAD components can well detect the change information of wetlands.

Key words: change detection, multivariate alteration detection(MAD), wetlands, object-oriented post-classification